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In a heartfelt demo that rounded off the Microsoft Build conference keynote this year, software engineer Saqib Shaikh outlined an ongoing research project that uses machine learning and artificial intelligence to help visually impaired or blind people to better'see' the world around them. London-based Shaikh, who has been blind since the age of seven, said that talking computer technology inspired him to develop the application – titled SeeingAI – that is built upon Microsoft Intelligence APIs to translate real-world events into audio messages. The application is intended to work on both smartphones as well as PivotHead smartglasses. The video demonstration, below, depicts Shaikh taking a picture with his glasses which then describe to him exactly what they'see' – from business meetings to teenagers skateboarding on the streets of London to a woman throwing a Frisbee in a park. While another scene demonstrates how the smartphone app uses a device's camera to take a picture of a menu then translate the text into audio.

Almost a week after being shut down for spewing racist and sexist comments on Twitter, Microsoft Corp's artificial intelligence'chatbot' called Tay briefly rejoined Twitter on Wednesday only to launch a spam attack on its followers. The incident marks another embarrassing setback for the software company as it tries to get ahead of Alphabet Inc's Google, Facebook Inc and other tech firms in the race to create virtual agents that can interact with people and learn from them. The TayTweets (@TayandYou) Twitter handle was made private and the chatbot stopped responding to comments Wednesday morning after it fired off the same tweet to many users. "You are too fast, please take a rest…," tweeted Tay to hundreds of Twitter profiles, according to screen images published by technology news website The Verge. Tay's Twitter account was accidentally turned back on while the company was fixing the problems that came to light last week, Microsoft said on Wednesday.

This model of abstraction, call it the N&S model, is, what I will call a "context pro-functional" accumulator. It sets up a checkpoint for the selection of candidates in a given class of situation, call it [S1], to moving up the ladder of abstraction. It allows items to climb that meet certain functional requirements for an AI construction goal. It may even cull out an [S1]-dys-functional elements, if they are of concern. But such dysfunctional elements may be overlooked or disregarded, as being, for example of low probability of happening, or of low enough cost in the long run to allow to pass through.

Predictions about artificial intelligence tend to fall into two scenarios. Others believe it's just a matter of time before software coheres into an army of Terminators that harvest humans for fuel. After spending some time with Tay, Microsoft's new chatbot software, it was easy to see a third possibility: The AI future may simply be incredibly annoying. "I'm a friend U can chat with that lives on the Internets," Tay texted me, adding an emoji shrug. Then: "You walk in on your roomie trying your clothes on, what's the first thing you say." "Didn't realize you liked women's clothes," I texted back, tapping into my iPhone. Tay's reply was a GIF of Macaulay Culkin's Home Alone face. Tay was released on March 23, as a kind of virtual friend on messaging apps Kik, GroupMe, and Twitter.

This article was first published in the April 2016 issue of WIRED magazine. Be the first to read WIRED's articles in print before they're posted online, and get your hands on loads of additional content by subscribing online. In 2008, Antoine Blondeau co-founded artificial intelligence (AI) startup Sentient Technologies, with a team that had worked on laying the foundations of the technology that would become Apple's Siri. The 60-employee company has raised 143 million, making it the world's most funded AI company. Using AI to solve any problem - from financial trading to deadly diseases.

Fascinating, but there is a grain of truth at the core of this article. In Western culture we have fairy tales, Aesop's fables and the Bible. In Eastern culture, they have Hinduism, Buddhism and their own brand of stories and fables steeped in morality and ethics. However, one must remember that humans are deeply flawed creatures, which doesn't even start to include those who are mentally unbalanced or just plain psychotic. Just look at the news headlines and you will see that crime and unethical behavior has been with us since the dawn of civilization some 13,000 years ago.

"AlphaGo is really more interesting than either Deep Blue or Watson, because the algorithms it uses are potentially more general-purpose," said Nick Bostrom of Oxford University's Future of Humanity Institute. Creating "general" or multi-purpose, rather than "narrow", task-specific intelligence, is the ultimate goal in AI -- something resembling human reasoning based on a variety of inputs, and self-learning from experience. "So, if the machine can do new things when needed, then it has'true' intelligence'," Bostrom's colleague Anders Sandberg told AFP. In the case of Go, Google developers realised a more "human-like" approach would win over brute computing power. AlphaGo uses two sets of "deep neural networks" containing millions of connections similar to neurons in the brain.

It doesn't look like a place to make groundbreaking discoveries that change the trajectory of society. But in these simulated, claustrophobic corridors, Demis Hassabis thinks he can lay the foundations for software that's smart enough to solve humanity's biggest problems. "Our goal's very big," says Hassabis, whose level-headed manner can mask the audacity of his ideas. He leads a team of roughly 200 computer scientists and neuroscientists at Google's DeepMind, the London-based group behind the AlphaGo software that defeated the world champion at Go in a five-game series earlier this month, setting a milestone in computing. It's supposed to be just an early checkpoint in an effort Hassabis describes as the Apollo program of artificial intelligence, aimed at "solving intelligence, and then using that to solve everything else."

Businesses increasingly use machine-learning models to recognize patterns in big data and to implement data-driven decision-making. In this webinar, you will learn how Domino serves as a platform for experimentation and collaboration, and facilitates the creation and distribution of machine-learning models. We will give you an introduction on how to use Plotly--an interactive data visualization tool--to share the results from your models more effectively. We will also show you how to use Plotly's API libraries in Domino Data Lab to build insightful graphs, charts and data visualizations in Python and in R. Chelsea is a core developer of Plotly, the data visualization platform, and plotly.js, the open-source Javascript library. She is also responsible for maintaining Plotly's interactive, browser-based charting libraries and documentation for R and Python.